library_name: fastvideo
license: other
license_name: source-model-licenses
license_link: https://huggingface.co/FastVideo/FastVideo-FastH3-Trim-8-Step
FastH3 Trim 8-step MLX INT6
Converted from FastVideo/FastVideo-FastH3-Trim-8-Step, revision
9edcb6511d5ff8dd1579e8eec8afee77e098b8d8, from the released BF16 transformer.
The transformer uses MLX affine INT6 weights, retained VSA gates, and a cached
rank-16 AdaLN ladder. The native NVFP4 text encoder is stored in MLX layout
without requantization. The 26-layer lightweight video VAE and audio VAE are
included. fastvideo_inference.json supplies the eight-forward schedule.
Use the Spark/Mac code in hao-ai-lab/FastVideo#1920. After downloading this snapshot to MODEL_ROOT, run:
from fastvideo.mlx_runtime.minimax_h3_pipeline import MiniMaxH3MLXPipeline
from pathlib import Path
root = Path("MODEL_ROOT")
pipeline = MiniMaxH3MLXPipeline(
model_root=root, mlx_dit_checkpoint=root / "transformer",
conditioner_mode="nvfp4", vae_dtype="fp16", resident=False,
metal_wired_limit_gib=27,
)
try:
pipeline.generate("A red fox in snow.", output_path="clip.mp4",
width=832, height=480, num_frames=124, seed=1234,
num_steps=8, vsa=True, vsa_sparsity=0.8,
vsa_tile_size=64, vsa_impl="reference")
finally:
pipeline.close()
Use reference attention for release generation. The optional SIMD Metal backend has a known partial-tile correctness issue. Phased placement keeps one heavy component loaded at a time on the 36 GiB Mac. Transformer storage is 15,355,458,984 bytes including its manifest, before the encoder and VAEs.
This is an experimental pruned model. Source-model licensing and acceptable-use terms still apply. See the source repository and its parent model licenses.